Quasi-Equilibrium Convection in a Global Cloud-Resolving Model

The quasi-equilibrium (QE) hypothesis suggests that convection acts quickly to consume convective instability generated by slower large-scale processes. Convection parameterizations in global models are often developed on the assumption that QE is correct at the grid scale, yet QE’s dependencies and relevant parameters are underexplored in global-scale data sets. In this study we employ global non-hydrostatic simulations from the NASA GEOS model to examine the assumptions of QE thinking. The GEOS simulations employ explicit, rather than parameterized, convection. Therefore, they serve as a useful tool for investigating the interplay between fast, small-scale convection and slow, large-scale dynamics. We show that precipitation and mass flux at a given location are proportional to the rate at which large-scale processes – such as radiation and surface fluxes - generate convective available potential energy (CAPE) there. This is consistent with QE thinking. We then quantify a time-scale of convection by isolating the adjustment of CAPE due to precipitation. This allows us to examine convection’s dependence upon the large-scale meteorology and provides a benchmark for comparison to models with parameterized convection.